Until now I used to convert all values in a pandas dataframe with combined numerical and string entries to numeric values if possible in one easy step, using .map and .to_numeric with "errors = 'ignore'". It worked perfectly, but after updating to the latest version of Pandas (2.2.3) I get a FutureWarning. import pandas as pd A = pd.DataFrame({ 'x' : ['1','2','3'], 'y' : ['not_a_number','5',9999], }) # example data B = A.map(pd.to_numeric, errors = 'ignore') # FutureWarning: errors='ignore' is deprecated and will raise in a future version. Use to_numeric without passing errors and catch exceptions explicitly instead B = A.map(pd.to_numeric, errors = 'ignore') How could I code this future proof in an elegant, vectorised way? I could not think of any solution that is not very cumbersome (looping over each individual entry of the dataframe). Continue reading...
